Neuro Fuzzy Models
Mostrando 1-12 de 20 artigos, teses e dissertações.
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1. NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
ABSTRACT Considering the challenges faced by poultry farming, this study aimed to develop a neuro-fuzzy model to predict eyeball and crest temperatures of egg-laying hens based on environmental conditions (dry bulb temperature and relative humidity). To develop the models and simulations, Matlab’s Fuzzy Toolbox® (Anfisedit) was used. Different configurati
Eng. Agríc.. Publicado em: 2021-02
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2. Local linear model tree and Neuro-Fuzzy system for modelling and control of an experimental pH neutralization process
This paper describes the modelling and control of a pH neutralization process using a Local Linear Model Tree (LOLIMOT) and an adaptive neuro-fuzzy inference system (ANFIS). The Direct and Inverse model building using LOLIMOT and ANFIS structures is described and compared. The direct and inverse models of the pH system are identified based on experimental da
Braz. J. Chem. Eng.. Publicado em: 2014-06
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3. Controle preditivo baseado em modelo neuro-fuzzy de sistemas não-lineares aplicado em sistema de refrigeração = : Model predictive control based on neuro-fuzzy nonlinear systems applied to a refrigeration plant / Model predictive control based on neuro-fuzzy nonlinear systems applied to a refrigeration plant
Refrigeration systems can be found in many different branches of industry and are characterized as great energy consumers with considerable non-linear behavior. Several studies have been developed to promote the reduction of energy costs and to minimize the effects of nonlinearities in these systems. The use of automation and process control, particularly th
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 03/07/2012
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4. Identificação fuzzy-multimodelos para sistemas não lineares
Este trabalho apresenta uma nova técnica de identificação multimodelos baseada em ANFIS para sistemas não lineares. Nesta técnica, a estrutura utilizada é do tipo fuzzy Takagi-Sugeno cujos consequentes são modelos lineares locais que representam o sistema em diferentes pontos de operação e os antecedentes são funções de pertinência cujos ajustes
Publicado em: 2010
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5. MODELOS NEURO-FUZZY HIERÁRQUICOS BSP DO TIPO 2 / TYPE-2 HIERARCHICAL NEURO-FUZZY BSP MODEL
The objective of this thesis is to create a new type-2 fuzzy inference system for the treatment of uncertainties with automatic learning and that provides an interval of confidence for its defuzzified output through the calculation of corresponding type-reduced sets. In order to attain this objective, this new model combines the paradigms of the modelling of
Publicado em: 2007
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6. Previsão de carga de curto prazo usando ensembles de previsores selecionados e evoluidos por algoritmos geneticos / Short-term load forecasting using esembles of selected and evolved predictors by genetic algorithms
This work proposes a methodology for short-term electric power load forecasting. This methodology is being widely used under the context of time series prediction and pattern recognition. It was named "ensembles" by the authors who developed it. This name carries the meaning of an assemblage of parts considered as forming a whole. Therefore, this name expres
Publicado em: 2006
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7. SISTEMA INTELIGENTE DE OTIMIZAÇÃO DE ALTERNATIVAS DE DESENVOLVIMENTO DE CAMPOS PETROLÍFEROS / INTELLIGENT SYSTEM FOR OPTIMIZATION OF ALTERNATIVES FOR PETROLEUM FIELDS DEVELOPMENT
This work investigates the problem of optimization of alternatives for petroleum fields` development. A development alternative refers to the way a well-known and delimited petroleum field is placed in production. This process involves the determination of the number, localization and scheduling of producer and injector wells. Thus, the optimization of alter
Publicado em: 2005
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8. DATA MINING APPLIED TO CUSTOMER RETENTION IN WIRELESS TELECOMMUNICATIONS / MINERAÇÃO DE DADOS NA RETENÇÃO DE CLIENTES EM TELEFONIA CELULAR
The goal of this work is to propose a complete data mining system for the solution of customer retention problems, commonly found in many industries. Such a solution encompasses the accurate identification among huge amounts of data of those consumers who would most likely end their relationship with the firm, based on their historical behavior and individua
Publicado em: 2005
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9. Desenvolvimento de uma plataforma hÃbrida para descoberta de conhecimento em bases de dados
Artificial Neural Networks (ANN) have successfully been used in tasks as the mapping of complex functions and pattern recognition. This success is due to the ANN ability to make calculations of complicated and undetermined data, learn from examples, generalize the learned information, extract patterns and discover tendencies. Despite these advantages, it is
Publicado em: 2004
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10. APLICAÇÕES DE TÉCNICAS BASEADAS NO SVD À ANÁLISE E PREVISÃO DE DADOS / APPLICATIONS OF TECHNIQUES BASED ON THE SVD TO THE ANALYSIS AND FORECAST OF DATA.
O objetivo do presente trabalho é desenvolver uma técnica para a modelagem de sistemas, capaz de se adaptar a uma larga classe de problemas. Como aspecto inovador esta a forma como é orientada a modelagem do sinal, feita segundo a análise dos espaços dos sinais de entrada e saída, destes analises são feitas partições iterativamente em tais espaços
Publicado em: 2004
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11. HIBRID NEURO-FUZZY-GENETIC SYSTEM FOR AUTOMATIC DATA MINING / SISTEMA HÍBRIDO NEURO-FUZZY-GENÉTICO PARA MINERAÇÃO AUTOMÁTICA DE DADOS
This dissertation presents the proposal and the development of a totally automatic data mining system. The main objective is to create a system that is capable of extracting obscure information from complex databases, without demanding the presence of a technical specialist to configure it. The Hierarchical Neuro-Fuzzy Binary Space Partitioning model (NFHB)
Publicado em: 2004
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12. HIERARQUICAL NEURO-FUZZY MODELS BASED ON REINFORCEMENT LEARNING FOR INTELLIGENT AGENTS / NOVOS MODELOS NEURO-FUZZY HIERÁRQUICOS COM APRENDIZADO POR REFORÇO PARA AGENTES INTELIGENTES
This thesis investigates neuro-fuzzy hybrid models for automatic learning of actions taken by agents. The objective of these models is to provide an agent with intelligence, making it capable of acquiring and retaining knowledge and of reasoning (infer an action) by interacting with its environment. Learning in these models is performed by a non-supervised p
Publicado em: 2003